1. Technical Field
The present disclosure relates generally to selecting digital fonts. More specifically, one or more embodiments of the present disclosure relate to systems and methods that detect digital fonts of digital text in an electronic document and automatically identify complementary digital fonts based on the detected digital fonts.
2. Background and Relevant Art
Recent years have seen a rapid proliferation in the use of mobile devices in creating and editing electronic documents. Indeed, with the ubiquitous use of tablets and smartphones for both personal and business purposes, individuals and businesses are increasingly generating and modifying electronic documents utilizing mobile devices. For example, individuals and businesses routinely utilize mobile devices to create digital marketing materials, digital magazines, webpages, e-mails, and other electronic documents.
Recent years have also seen an increase in digital fonts utilized in electronic documents. For instance, some contemporary digital editing systems provide access to thousands of digital fonts for utilization in conjunction with various electronic documents. Accordingly, individuals and businesses can now access and utilize a wide variety of different digital fonts in generating and modifying electronic documents.
Although the increased number of digital fonts provides numerous options and flexibility for users, the sheer number of digital fonts can also create problems. For example, users often experience frustration in trying to identify digital fonts utilizing conventional digital editing systems. Indeed, searching through thousands of digital fonts offered by conventional digital editing systems requires a significant amount of time and effort, and often leads to irritation and dissatisfaction.
User frustration is often exacerbated with regard to conventional digital editing systems operating on mobile devices (e.g., tablets or smartphones). For instance, mobile devices have more limited processing power, reduced multi-tasking capabilities, additional limitations with regard to user interfaces (e.g., mobile devices cannot generally provide multiple simultaneous windows), and more limited memory constraints (e.g., insufficient space for thousands of digital fonts). Thus, for example, a user searching for digital fonts on a smartphone with a touchscreen has more limited screen space to utilize than a traditional desktop computing device. Accordingly, searching for and selecting digital fonts with regard to mobile devices can take additional time and effort and lead to additional frustration and dissatisfaction.
These and other problems exist with regard to current techniques for identifying and using digital fonts.